Analyzing And Visualizing Ancient Maya Hieroglyphics Using Shape: From Computer Vision To Digital Humanities

Maya hieroglyphic analysis requires epigraphers to spend a significant amount of time browsing existing catalogs to identify individual glyphs. Automatic Maya glyph analysis provides an efficient way to assist scholars' daily work. We introduce the Histogram of Orientation Shape Context (HOOSC) shape descriptor to the Digital Humanities community. We discuss key issues for practitioners and study the effect that certain parameters have on the performance of the descriptor. Different HOOSC parameters are tested in an automatic ancient Maya hieroglyph retrieval system with two different settings, namely, when shape alone is considered and when glyph co-occurrence information is incorporated. Additionally, we developed a graph-based glyph visualization interface to facilitate efficient exploration and analysis of hieroglyphs. Specifically, a force-directed graph prototype is applied to visualize Maya glyphs based on their visual similarity. Each node in the graph represents a glyph image; the width of an edge indicates the visual similarity between the two according glyphs. The HOOSC descriptor is used to represent glyph shape, based on which pairwise glyph similarity scores are computed. To evaluate our tool, we designed evaluation tasks and questionnaires for two separate user groups, namely, a general public user group and an epigrapher scholar group. Evaluation results and feedback from both groups show that our tool provides intuitive access to explore and discover the Maya hieroglyphic writing, and could potentially facilitate epigraphy work. The positive evaluation results and feedback further hint the practical value of the HOOSC descriptor.